一种电力系统无功优化的新型混合优化算法

摘要

提出了一种适合于求解电力系统无功优化问题的新型混合优化算法,该算法结合基于邻域搜索的群搜索优化算法和改进灾变遗传算法.综合考虑两种算法的特点,将无功优化问题分步进行交替求解,第一步采用改进灾变遗传算法迭代两次更新解群体,第二步在此基础上采用基于邻域搜索的群搜索优化算法使群体中各解向当前最优解靠拢,交替进行,最终达到全局最优解.在IEEE118节点系统试验计算结果表明,与其他算法相比,该混合算法具有较好的全局收敛性且不容易陷入局部最优,在优化效果以及算法稳定度上都具有明显的优势.在某实际290节点电网计算结果表明,该混合算法能够适应实际电力系统无功优化问题的求解.%Based on the group search optimizer with neighborhood search (NGSO) and the improved catastrophic genetic algorithm(ICGA), this paper proposes a novel hybrid algorithm for solving reactive-power optimization of power system. Considering the characteristics of the two kinds of algorithms, the reactive power optimization will be solved by improved sequential method, which adopts ICGA twice to update the solutions first and then NGSO is used to make the solutions closer to the current optimal solution, and then alternates to get the global optimal solution. When it is tested in IEEE118-bus system, the hybrid algorithm has competitive superiority to other algorithms in terms of global performance and local optimum search, especially on the optimization effect and stability. The hybrid algorithm is also applied to the actual 290-bus grid. The promising results illustrate the applicability of hybrid algorithm for solving reactive-power optimization of the actual power system.This work is supported by National Natural Science Foundation of China (No. 51077055).